Bibliographic record
Abstract
There has been considerable debate about the relevance and applicability of SLA theory and research for L2 pedagogy. There are those who maintain that SLA must be applicable to L2 pedagogy: a view based on the argument that because SLA is a subfield of applied linguistics, it should have direct relevance to L2 teaching. Others take the view that not all areas of SLA research need to be relevant to L2 pedagogy – only the more ‘applied’ areas. While I would agree that much of the work in SLA should be applicable to L2 pedagogy, particularly research on instructed SLA, my presentation takes a different perspective on the SLA/L2 pedagogy interface. It focuses onmisapplicationsof SLA theory and research to L2 pedagogy. I argue that the applicability of SLA research for L2 instruction requires a careful consideration of context and that specific SLA constructs – even those considered to be important within instructed SLA – may not have directrelevanceto L2 pedagogy. Three areas of SLA research that I will discuss with respect to misapplication and relevance are: the role of instruction in SLA, the role of age in SLA, and the nature of and distinction between implicit and explicit L2 knowledge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.199 | 0.383 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.008 | 0.110 |
| Scholarly communication | 0.023 | 0.054 |
| Open science | 0.007 | 0.027 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".